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Abstract

A robust body of neurophysiologic research is reviewed on functional brain abnormalities associated with depression, anxiety, and obsessive-compulsive disorder. A review of more recent research finds that pharmacologic treatment may not be as effective as previously believed. A more recent neuroscience technology, electroencephalographic (EEG) biofeedback (neurofeedback), seems to hold promise as a methodology for retraining abnormal brain wave patterns. It has been associated with minimal side effects and is less invasive than other methods for addressing biologic brain disorders. Literature is reviewed on the use of neurofeedback with anxiety disorders, including posttraumatic stress disorder and obsessive-compulsive disorder, and with depression. Case examples are provided.
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Neurofeedback with Anxiety and Affective Disorders
Journal of Child & Adolescent Psychiatry Clinics of North
America, Jan. ‘05
(This article has been lightly edited by David Dubin, MD to make it more accessible to a
general public.)
D. Corydon Hammond, PhD, ABEN/ECNS
Physical Medicine and Rehabilitation, University of Utah School of Medicine,
Compelling evidence exists for a neurophysiologic basis for obsessive-
compulsive disorder (OCD). There is also strong research evidence also
indicates that there are functional brain abnormalities associated with anxiety and
panic disorder [28–30] and post- traumatic stress disorder (PTSD) [31].
There is a strong reliance in psychiatry on the use of medication for the treatment
of depression and anxiety, although some evidence currently suggests that
medication may not be as effective in treating these conditions as has often been
believed [44–48].
Similarly, Greist [49] estimated the degree of symptomatic improvement in OCD
from treatment with serotonin drugs to only be 30%. Goodman et al [44] similarly
found that symptom amelioration in OCD treatment with serotonin uptake
inhibitors is approximately 35% on average and that only 50% of patients
experience this partial improvement.
In light of this brief review and the fact that an increasing number of patients and
parents seem interested in non- medication treatment alternatives that still
address the underlying biologic factors associated with depression, anxiety, and
obsessive compulsive disorder (OCD), it would be desirable to find a treatment
that also would help address the biologic aspects of mental health disorders.
Neurofeedback holds promise for offering such an alternative.
What is neurofeedback?
Neurofeedback is EEG biofeedback or brain wave training. Nothing intrusive is
introduced into the brain. The sensors simply measure the ongoing brain wave
activity.
Ordinarily we are unable to reliably influence our brain wave activity because we
lack awareness of it. When we are able to see representations of our brain wave
activity on a computer screen a few thousandths of a second after it occurs,
however, it allows us to modify our brain wave patterns through operant
2
conditioning.
The patient is placed in front of a computer screen. The computer display may
be as complex as a computer/video game type of display. It also may be as
simple as two bar graphs, one representing slow and inefficient brain wave
activity and the other representing efficient, beta brain wave activity. The patient
concentrates on the screen. When the inappropriate activity decreases slightly
and the appropriate activity increases slightly, a pleasant tone might be heard.
At first, changes in brain wave activity are transient. As sessions are repeated,
enduring changes are gradually seen.
EEG biofeedback (neurofeedback) has been found to be effective in modifying
brain function and producing significant improvements in clinical symptoms in
children, adolescents, and adults who have several different biologic brain
disorders.
These conditions include epilepsy, attention deficit disorder and attention deficit
hyperactivity disorder (ADHD), and learning disabilities and have included up to
10-year follow-ups of patients [57].
Neurofeedback for anxiety
A review of the literature on the neurofeedback treatment of anxiety disorders by
Moore [58] identify eight studies of generalized anxiety disorder.
The best studies of neurofeedback with anxiety were three outcome studies [59]
with phobic (test) anxiety. In each study, the group that received alpha EEG
enhancement training demonstrated significant reductions in test anxiety. In
comparison, the untreated control group and the relaxation training group
experienced no significant reduction.
In another study, with alpha training the anxiety scores dropped significantly
compared with a non-treatment group. Moore [58] concluded in his review that a
placebo effect was present in these neurofeedback studies but that alpha and
theta enhancement training provided additional effects beyond placebo and are
effective treatments for anxiety disorders.
Passini et al [70] used 10 hours of alpha neurofeedback training, comparing 25
anxious patients (23 of whom were alcoholics) with a control group of 25 anxious
patients (22 of whom were also alcoholics), most of whom were seeking
treatment at a Veterans Administration hospital brief treatment unit. The alpha
neurofeedback training produced significant changes in state and trait anxiety
compared with controls.
An 18-month follow-up of those patients was published, with virtually identical
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results of lower anxiety still found, which validated that the anxiety changes from
alpha neurofeedback were enduring [71].
Two neurofeedback outcome studies have focused on chronic PTSD. In a
randomized, controlled group study [73], 30 30-minute sessions of alpha-theta
EEG biofeedback training were added to the traditional Veterans Administration
hospital treatment that was provided to a group of 15 Vietnam combat veterans
with PTSD. The study compared them after treatment and at follow-up with a
contrast group of 14 veterans who only received traditional treatment.
In addition to the posttreatment testing, on a monthly basis, patients and
informers were contacted for a full 30-month follow-up period to determine if
there had been PTSD symptoms (eg, flashbacks, nightmares, anxiety attacks,
depression).
At follow-up, all 14 traditional treatment patients had experienced relapse,
whereas only 3 of 15 neurofeedback training patients had experienced relapse.
All 14 patients who were treated with neurofeedback had decreased their
medication requirements at follow-up, whereas in contrast, only 1 traditional
treatment patient had decreased medication needs, 2 reported no change, and
10 required more medications.
Neurofeedback training patients improved significantly on all ten MMPI clinical
scales—in many in- stances dramatically—but there were no significant
improvements on any scales in the traditional treatment group.
In another Veterans Administration hospital uncontrolled study [74], 20 Vietnam
veterans with chronic PTSD, all with alcohol abuse, were randomly selected. All
patients showed frequent (eg, two to three times per week) episodes of PTSD
and had been hospitalized for PTSD an average of five times.
They were treated with 30 30-minute sessions of alpha- theta neurofeedback
training. Follow-up interviews occurred with the patients and their wives or family
members on a monthly basis for 26 months. In that time, only 4 of the 20 patients
reported a few (one to three) instances of recurrence of nightmares or
flashbacks, and the other 16 patients had no recurrence of PTSD symptoms.
Neurofeedback for depression
Although reports to date on the application of neurofeedback to depression
only represent uncontrolled case reports, they provide encouragement that
neurofeedback may hold potential for treating mildly to severely depressed
patients and that unlike medication, it may enduringly modify the functional brain
abnormality associated with biologic predisposition to depression.
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Clinical experience and further case examples
Based on clinical experience with more than 25 patients with dysthymia, in
which most of them have been followed for between 6 and 24 months,
neurofeedback has seemed to be successful in producing significant and
enduring change in approximately 80% of the patients. There have been no
published research or clinical reports on the use of neurofeedback in a pediatric
depression sample. Because the biologic marker of a frontal alpha asymmetry
has been found in multiple studies with children and infants [38–41] of depressed
mothers, and because there is abundant evidence that children respond to
neurofeedback training for other conditions, it is reasonable to expect that this
approach would be beneficial with depressed children.
There are widespread clinical reports of improvements in mood among children
treated with neurofeedback for ADHD, which further supports the expectation
that neurofeedback may be effective with childhood depression. There also are
reports of improvements in bipolar disorder.
Neurofeedback seems to involve minimal risk of side effects or adverse reactions
[84], and it is less invasive than antidepressant medication or transcranial
magnetic stimulation.
Anxiety and insomnia
In most cases, anxiety and insomnia are readily treated with neurofeedback
[58,59,85–88]. One of the first improvements that parents often notice is that the
child falls asleep more easily and remains asleep. With anxiety patients,
neurofeedback training often is done eyes closed while listening to auditory
feedback, and in a sense it resembles high-technologic meditation training.
As a case example, a patient was referred by a physician who was a headache
specialist, indicating that everything that could be done with medication seemed
to have been done. The patient had a lengthy history of several migraines
weekly, which had progressed to daily migraines. She had been given a self-
hypnosis tape to use for anxiety management, but she complained that her mind
was so busy that she was unable to obtain much relaxation from the tape. After
20 30-minute sessions of inhibiting fast beta and reinforcing alpha activity in the
parietal area, she was off all her prescription medications. She sensed a
migraine trying to begin approximately twice weekly but would take over-the-
counter medication and could use the self-hypnosis tape successfully to abort the
headache. She felt more relaxed in general and reported no longer feeling
compelled to do two things at once.
5
Summary
As reviewed in other articles, the neuroscience technology known as EEG
biofeedback (or neurofeedback) has considerable research support in areas such
as uncontrolled epilepsy and attention deficit disorder and ADHD. In evaluating
the studies in the overall broad area of the neurofeedback treatment of anxiety
disorders, EEG biofeedback qualifies for the evidence-based designation of
being an efficacious treatment [62]. When separate anxiety disorders are
individually evaluated, the areas of phobic anxiety, generalized anxiety, and
PTSD each qualify for designation as being a probably efficacious treatment.
Currently there are only reports of cases and series of cases on the treatment of
depression and OCD and no published reports thus far on treatment of bipolar
disorder. Despite the lengthy follow-ups and use of objective measures,
neurofeedback treatment for depression and OCD is not yet empirically
supported. EEG biofeedback is an exciting, cutting-edge technology that offers
an additional treatment alternative for modifying dysfunctional, biologic brain
patterns that are associated with various psychiatric conditions.
References
[1] Baxter L, Phelps M, Mazziotta J. Local cerebral glucose metabolic rates in
obsessive-compulsive disorder: a comparison with rates in unipolar depression
and in normal controls. Arch Gen Psychiatry 1988;44:211 – 8.
[2] Baxter L, Phelps M, Mazziotta J, Guze BH, Schwartz JM, Selin C. Local
cerebral glucose metabolic rates in obsessive-compulsive disorder. Arch Gen
Psychiatry 1987;44:211 – 8.
[3] Benkelfat C, Phelps M, Mazziotta J, Guze BH, Schwartz JM, Selin RM. Local
cerebral glucose metabolic rates in obsessive-compulsive disorder patients
treated with clomipramine. Arch Gen Psychiatry 1990;147:846 – 8.
[4] Harris GJ, Pearlson GD, Hoehn-Saric R. Single photon emission computer
tomography in obsessive-compulsive disorder. Arch Gen Psychiatry
1993;50(6):498 – 501.
[5] Machlin SR, Harris GJ, Pearlson GD. Elevated medial-frontal cerebral blood
flow in obsessive- compulsive patients: a SPECT study. Am J Psychiatry
1991;148:1240 – 2.
[6] Nordahl TE, Benkelfat C, Semple WE, Gross M, King AC, Cohen RM.
Cerebral glucose metabolic rates in obsessive-compulsive disorder.
Neuropsychopharma 1989;2:23 – 8.
[7] Perani D, Colombo C, Bressi S, Bonfanti A, Grassi F, Scarone S, et al.
18[F]FDG PET study in obsessive-compulsive disorder: a clinical/metabolic
correlation study after treatment. Br J Psychiatry 1995;156:244 – 50.
[8] Piacentini J, Bergman RL. Obsessive-compulsive disorder in children.
Psychiatr Clin N Am 2000;23(3):519 – 33.
[9] Rauch SL, Whalen PJ, Dougherty D, Jenike MA. Neurobiologic models of
obsessive-
6
compulsive disorder. In: Jenike MA, Baer WE, Minichiello WE, editors.
Obsessive-compulsive disorders: practical management. St. Louis7 Mosby;
1998. p. 222 – 53.
[10] Rubin RT, Villaneuva-Meyer J, Anath J. Regional 133Xe cerebral blood flow
and cerebral 99m- HMPAO uptake in unmedicated obsessive-compulsive
disorder patients and matched normal control subjects: determination by high-
resolution single-photon emission computed tomography. Arch Gen Psychiatry
1992;49:695 – 702.
[11] Sawle GV, Hymas NF, Lees AJ. Obsessive slowness: functional studies with
positron emission tomography. Brain 1991;114:2191 – 202.
D.C. Hammond / Child Adolesc Psychiatric Clin N Am 14 (2005) 105–123 119
[12] Saxena S, Brody AL, Schwartz JM, Baxter LR. Neuroimaging and frontal-
subcortical circuitry in obsessive-compulsive disorder. Br J Psychiatry
1998;35:26 – 38.
[13] Swedo SE, Schapiro MG, Grady CL. Cerebral glucose metabolism in
childhood onset obsessive- compulsive disorder. Arch Gen Psychiatry
1989;46:518 – 23.
[14] Szeszko PR, Robinson D, Alvir JM, Bilder RM, Lencz T, Ashtari M, et al.
Orbital frontal and amygdala volume reductions in obsessive-compulsive
disorder. Arch Gen Psychiatry 1999; 56(10):913 – 9.
[15] Kuskowski MA, Malone SM, Kim SW, Dysken MW, Okaya AJ, Christensen
KJ. Quantitative EEG in obsessive-compulsive disorder. Biol Psychiatry
1993;33:423 – 30.
[16] Leocani L, Locatelli M, Bellodi L, Fornara C, Henin M, Magnani G, et al.
Abnormal pattern of cortical activation associated with voluntary movement in
obsessive-compulsive disorder: an EEG study. Am J Psychiatry 2001;158(1):140
– 2.
[17] Mas F, Prichep LS, John ER, et al. Neurometric quantitative
electroencephalogram subtyping of obsessive compulsive disorders. In: Mauer K,
editor. Imaging of the brain in psychiatry and related fields. Berlin7 Springer-
Verlag; 1993. p. 277 – 80.
[18] Perros R, Young E, Ritson J, Price G, Mann P. Power spectral EEG analysis
and EEG variability in obsessive-compulsive disorder. Brain Topogr
1992;4(3):187 – 92.
[19] Prichep LS, Mas F, John ER, et al. Neurometric subtyping of obsessive
compulsive disorders in psychiatry: a world perspective. In: Stefanis CN,
Rabavilas AD, Soldatos CR, editors. Pro- ceedings of the VIII World Congress of
Psychiatry. Athens, October 12–19, 1989. New York: Elsevier Science; p. 557–
62.
[20] Prichep LS, Mas F, Hollander E, Liebowitz M, John ER, Almas M, et al.
Quantitative
electroencephalography (QEEG) subtyping of obsessive compulsive disorder.
Psychiatr Res 1993;50(1):25 – 32.
[21] Silverman JS, Loychik SG. Brain-mapping abnormalities in a family with
three obsessive- compulsive children. J Neuropsychiatr Clin Neurosci 1990;2:319
– 22.
7
[22] Simpson HB, Tenke CE, Towey JB, Liebowitz MR, Bruder GE. Symptom
provocation alters behavioral ratings and brain electrical activity in obsessive-
compulsive disorder: a preliminary study. Psychiatr Res 2000;95(2):149 – 55.
[23] Gehring WJ, Himle J, Nisenson LG. Action-monitoring dysfunction in
obsessive-compulsive disorder. Psychol Sci 2000;11:1 – 6.
[24] Hajcak G, Simons RF. Error-related brain activity in obsessive-compulsive
undergraduates. Psychiatry Res 2002;110:63 – 72.
[25] Malloy P, Rasmussen S, Braden W, Haier RJ. Topographic evoked potential
mapping in obsessive-compulsive disorders: evidence of frontal lobe dysfunction.
Psychiatry Res 1989; 28(1):63 – 71.
[26] Posner MI, Rothbart MK. Attention, self-regulation and consciousness.
Philos Trans R Soc Lond B Biol Sci 1998;353:1 – 13.
[27] Ursu S, van Veen V, Siegle G, MacDonald A, Stenger A, Carter C. Executive
control and self- evaluation in obsessive-compulsive disorder: an event-related
fMRI study. Presented at the Cognitive Neuroscience Society Meeting. New
York, March 2001.
[28] Heller W, Etienne MA, Miller GA. Patterns of perceptual asymmetry in
depression and anxiety: implications for neuropsychological models of emotion
and psychopathology. J Abnorm Psychol 1995;104:327 – 33.
[29] Heller W, Nitschke JB, Etienne MA, Miller GA. Patterns of regional brain
activity differentiate types of anxiety. J Abnorm Psychol 1997;106(3):376 – 85.
[30] Wiedemann G, Pauli P, Dengler W, Lutzenberger W, Birbaumer N,
Buckkremer G. Frontal brain asymmetry as a biological substrate of emotions in
patients with panic disorders. Arch Gen Psychiatry 1999;56:78 – 84.
[31] Brown D, Scheflin AW, Hammond DC. Memory, trauma treatment, and the
law. New York7 WW Norton; 1998.
[32] Davidson RJ. Affective style and affective disorders: perspectives from
affective neuroscience. Cognition and Emotion 1998;12:307 – 30.
[33] Davidson RJ. Emotion and affective style: hemispheric substrates. Psychol
Sci 1992;3:39 – 43.
[34] Davidson RJ. Cerebral asymmetry, emotion and affective style. In: Davidson
RJ, Hugdahl K, editors. Brain asymmetry. Boston7 MIT Press; 1995. p. 361 – 87.
[35] Baehr E, Rosenfeld JP, Baehr R. The clinical use of an alpha asymmetry
protocol in the neurofeedback treatment of depression: two case studies. J
Neurotherapy 1997;2(3):10 – 23.
[36] Rosenfeld JP, Cha G, Blair T, Gotlib I. Operant biofeedback control of left-
right frontal alpha power differences. Biofeedback Self Regul 1995;20:241 – 58.
[37] Henriques JB, Davidson RJ. Left frontal hypoactivation in depression. J
Abnorm Psychol 1991; 100:534 – 45.
[38] Dawson G, Grofer Klinger L, Panagiotides H, Hill D, Spieker S. Frontal lobe
activity and affective behavior of infants of mothers with depressed symptoms.
Child Dev 1992;63:725 – 37.
[39] Dawson G, Grofer Klinger L, Panagiotides H, Spieker S, Frey K. Infants of
mothers with de- pressed symptoms: electroencephalographic and behavioral
findings related to attachment status. Dev Psychopathol 1992;4:67 – 80.
[40] Field T, Fox N, Pickens J, Nawrocki R. Relative right frontal EEG activation
8
in 3- to 6-month- old infants of ‘‘depressed’’ mothers. Dev Psychopathol
1995;26:7 – 14.
[41] Jones NA, Field T, Fox NA, Lundy B, Davalos M. EEG activation in 1-month-
old infants of depressed mothers. Dev Psychopathol 1997;9:491 – 505.
[42] Henriques JB, Davidson RJ. Regional brain electrical asymmetries
discriminate between previously depressed and health control subject. J Abnorm
Psychol 1990;99:22 – 31.
[43] Davidson RJ. Anterior electrophysiological asymmetries, emotion, and
depression: Conceptual and methodological conundrums. Psychophysiology
1998;35:607 – 14.
[44] Goodman WK, McDougle CJ, Price LH. Pharmacotherapy of obsessive
compulsive disorder. J Clin Psychiatry 1992;53(Suppl):29 – 37.
[45] Goodman WK, Price LH, Rasmussen SA, Mazure C, Fleischmann RL, Hill
CL, et al. The Yale- Brown obsessive ompulsive scale. I. Development, use, and
reliability. Arch Gen Psychiatry 1989;46:1006 – 11.
[46] Goodman WK, Pricee LH, Rasmussen SA, Mazure C, Delgado P, Heninger
GR, et al. The Yale- Brown obsessive compulsive scale. II. Validity. Arch Gen
Psychiatry 1989;46:1012 – 6.
[47] Jenike MA, Baer L, Ballantine T, Martuza RL, Tynes S, Giriunas I, et al.
Cingulotomy for refractory obsessive-compulsive disorder: a long-term follow-up
of 33 patients. Arch Gen Psychiatry 1991;48:548 – 55.
[48] Hughes JR, John ER. Conventional and quantitative electroencephalography
in psychiatry. J Neuropsychiatr Clin Neurosci 1999;11(2):190 – 208.
[49] Greist JH. Treatment of obsessive compulsive disorder: psychotherapies,
drugs, and other somatic treatment. J Clin Psychiatr 1990;51(8):44 – 50.
[50] Ackerman DL, Greenland S. Multivariate meta-analysis of controlled drug
studies for obsessive- compulsive disorder. J Clin Psychopharmacol
2002;22(3):309 – 17.
[51] Rauch SL. Neuroimaging research and the neurobiology of obsessive-
compulsive disorder: where do we go from here? Biol Psychiatry 2000;47:168 –
70.
[52] DeRubeis RJ, Gelfand LA, Tang TZ, Simons AD. Medications versus
cognitive behavior therapy for severely depressed outpatients: mega-analysis of
four randomized comparisons. Am J Psychiatry 1999;156:1007 – 13.
[53] Antonuccio DO, Danton WG, DeNelsky G. Psychotherapy vs. medication for
depression: challenging the conventional wisdom with data. Professional
Psychology: Research and Practice 1995;26:574 – 85.
[54] Hollon SD, Shelton RC, Loosen PT. Cognitive therapy and pharmacotherapy
for depression. J Consult Clin Psychol 1991;59:88 – 99.
[55] Foa EB, Franklin ME. Obsessive-compulsive disorder. In: Barlow DH, editor.
Clinical handbook of psychological disorders. 3rd edition. New York7 Guilford
Press; 2001. p. 209 – 63.
[56] Whitsett SF, Lubar JF, Holder GS, et al. A double-blind investigation of the
relationship between seizure activity and the sleep EEG following EEG
biofeedback training. Biofeedback Self Regul 1982;7:183 – 209.
[57] Lubar JF. Neurofeedback for the management of attention
9
deficit/hyperactivity disorders. In: Schwartz MS, editor. Biofeedback: a
practitioner ’s guide. New York7 Guilford Press; 1995. p. 493 – 522.
[58] Moore NC. A review of EEG biofeedback treatment of anxiety disorders. Clin
Electro-
encephalogr 2000;31(1):1 – 6.
[59] Garrett BL, Silver MP. The use of EMG and alpha biofeedback to relieve test
anxiety in college students. In: Wickramasekera I, editor. Biofeedback, behavior
therapy, and hypnosis. Chicago7 Nelson-Hall; 1976.
[60] Chambless DL, Baker MJ, Baucaom DH, Beutler LE, Calhoun KS, Crits-
Christoph P, et al. Update on empirically validated therapies. Clin Psychol
1998;51(1):3 – 16.
[61] Chambless D, Hollon SD. Defining empirically supported therapies. J
Consult Clin Psychol 1998;66:7 – 18.
[62] La Vaque TJ, Hammond DC, Trudeau D, Monastra V, Perry J, Lehrer P.
Template for developing guidelines for the evaluation of the clinical efficacy of
psychophysiological interventions. J Neurotherapy 2002;6(4):11 – 23.
[63] Benson K, Hartz AJ. A comparison of observational studies and randomized,
controlled trials. N Engl J Med 2000;342(25):1878 – 86.
[64] Concato J, Shah N, Horwitz RI. Randomized, controlled trials, observational
studies, and the hierarchy of research designs. N Engl J Med 2000;342(25):1887
– 92.
[65] Britton A, McPherson K, KcKee M, Sanderson C, Black N, Bain C. Choosing
between
randomized and non-randomized studies: a systematic review. Health Technol
Assess 1998;
2(13):1 – 124. [66] Lurie P, Wolfe S. Unethical trials of interventions to reduce
perinatal transmission of the human immunodeficiency virus in developing
countries. N Engl J Med 1997;337(12):853 – 6.
[67] Rothman DJ. Ethical and social issues in the development of new drugs and
vaccines. Bull N Y Acad Med 1987;63(6):557 – 68.
[68] La Vaque TJ, Rossiter T. The ethical use of placebo controls in clinical
research: the Declaration of Helsinki. Appl Psychophysiol Biofeedback
2001;26(1):23 – 37.
[69] Linden M, Habib T, Radojevic V. A controlled study of the effects of EEG
biofeedback on cognition and behavior of children with attention deficit disorder
and learning disabilities. Biofeedback Self Regul 1996;21(1):35 – 49.
[70] Passini FT, Watson CG, Dehnel L, Herder J, Watkins B. Alpha wave
biofeedback training therapy in alcoholics. J Clin Psychol 1977;33(1):292 – 9.
[71] Watson CG, Herder J, Passini FT. Alpha biofeedback therapy in alcoholics:
an 18-month follow-up. J Clin Psychol 1978;34(2):765 – 9.
[72] Egner T, Gruzelier JH. Ecological validity of neurofeedback: modulation of
slow wave EEG enhances musical performance. Neuroreport 2003;14(9):1221 –
4.
[73] Peniston EG, Kulkosky PJ. Alpha-theta brainwave neuro-feedback therapy
for Vietnam veterans with combat-related post-traumatic stress disorder. Medical
Psychotherapy 1991;4:47 – 60.
10
[74] Peniston EG, Marrinan DA, Deming WA, Kulkosky PJ. EEG alpha-theta
synchronization in Vietnam theater veterans with combat-related post-traumatic
stress disorder and alcohol abuse. Advances in Medical Psychotherapy
1993;6:37 – 50.
[75] Hammond DC. QEEG-guided neurofeedback in the treatment of obsessive
compulsive disorder. Journal of Neurotherapy 2003;7(2):25 – 52.
[76] Hammond DC. Treatment of obsessional OCD with neurofeedback.
Biofeedback 2004;32:9 – 12. [77] Rosenfeld JP. EEG biofeedback of frontal
alpha asymmetry in affective disorders. Biofeedback 1997;25(1):8 – 25.
[78] Baehr E, Rosenfeld JP, Baehr R. Clinical use of an alpha asymmetry
neurofeedback protocol in the treatment of mood disorders: follow-up study one
to five years post therapy. Journal of Neurotherapy 2001;4(4):11 – 8.
[79] Allen JJ, Iacono WG, Depue RA, Arbisi P. Regional electroencephalographic
asymmetries in bipolar seasonal affective disorder before and after exposure to
bright light. Biol Psychiatry 1993;33:642 – 6. D.C. Hammond / Child Adolesc
Psychiatric Clin N Am 14 (2005) 105–123 122
[80] Gotlib IH, Ranganath C, Rosenfeld JP. Frontal EEG alpha asymmetry,
depression, and cognitive functioning. Cognition and Emotion 1999;12:449 – 78.
[81] Kwon JS, Youn T, Jung HY. Right hemisphere abnormalities in major
depression: quantitative electroencephalographic findings before and after
treatment. J Affect Disord 1996;40:169 – 73.
[82] Hammond DC. Neurofeedback treatment of depression with the Roshi.
Journal of Neurotherapy 2000;4(2):45 – 56.
[83] Hammond DC. Neurofeedback treatment of depression and anxiety. J Adult
Dev, in press.
[84] Hammond DC, Stockdale S, Hoffman D, Ayers ME, Nash J. Adverse
reactions and potential iatrogenic effects in neurofeedback training. Journal of
Neurotherapy 2001;4(4):57 – 69.
[85] Hardt JV, Kamiya J. Anxiety change through electroencephalographic alpha
feedback seen only in high anxiety subjects. Science 1978;201:79 – 81.
[86] Feinstein B, Sterman MB, MacDonald LR. Effects of sensorimotor rhythm
training on sleep. Sleep Research 1974;3:134.
[87] Sterman MB. Effects of sensorimotor EEG feedback on sleep and clinical
manifestations of epilepsy. In: Beatty J, Legewie H, editors. Biofeedback and
behavior. New York7 Plenum Press; 1977. p. 167 – 200.
[88] Sterman MB, Howe RD, Macdonald LR. Facilitation of spindle-burst sleep by
conditioning of electroencephalographic activity while awake. Science
1970;167:1146 – 8.
[89] Duffy FH. The state of EEG biofeedback therapy (EEG operant conditioning)
in 2000: an editor’s opinion [editorial]. Clin Electroencephalogr 2000;31(1):v – viii.
D.C. Hammond / Child Adolesc Psychiatric Clin N Am 14 (2005) 105–123 123
... Neurofeedback training (NFT) is considered a primary or supplementary treatment for a number of disorders, including attention-deficit/hyperactivity disorder (ADHD) [1][2][3][4][5], anxiety [6][7][8][9], and depression [7,8,10]. The American Academy of Pediatrics [11] provided a "level 1 best support" rating of NFT as a safe and effective evidence-based therapy for childhood ADHD. ...
... Neurofeedback training (NFT) is considered a primary or supplementary treatment for a number of disorders, including attention-deficit/hyperactivity disorder (ADHD) [1][2][3][4][5], anxiety [6][7][8][9], and depression [7,8,10]. The American Academy of Pediatrics [11] provided a "level 1 best support" rating of NFT as a safe and effective evidence-based therapy for childhood ADHD. ...
... Independent-samples t tests were conducted for each power ratio across groups (ie, healthy and abnormal values). Frequency bands were defined as follows: delta (1-4 Hz), theta (4-8 Hz), alpha (8)(9)(10)(11)(12)(13), and beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). These were averaged across frontal electrodes (ie, F3 and F4, based on the frontal nodes of the frontoparietal network [25,72] and the prevalence of a clean EEG signal) during the eyes-closed condition. ...
Preprint
BACKGROUND Neurofeedback training (NFT) has been shown to be effective in treating several disorders (eg, attention-deficit/hyperactivity disorder [ADHD], anxiety, and depression); however, little is currently known regarding the effectiveness of remote NFT systems. OBJECTIVE This retrospective study provides real-world data (N=593) to assess the efficacy of app-based remote NFT in improving brain health and cognitive performance. METHODS Improvement was measured from pre- to postintervention of in-app assessments that included validated symptom questionnaires (the 12-item General Health Questionnaire, the ADHD Rating Scale IV, the Adult ADHD Self-Report Scale, the 7-item Generalized Anxiety Disorder scale, and the 9-item Patient Health Questionnaire), a cognitive test of attention and executive functioning (ie, continuous performance task), and resting electroencephalography (EEG) markers. Clinically significant improvement was evaluated using standard approaches. RESULTS The greatest improvement was reported for the anxiety questionnaire, for which 69% (68/99) of participants moved from abnormal to healthy score ranges. Overall, adult and child participants who engaged in neurofeedback to improve attention and executive functions demonstrated improved ADHD scores and enhanced performance on a cognitive (ie, response inhibition) task. Adults with ADHD additionally demonstrated elevated delta/alpha and theta/alpha ratios at baseline and a reduction in the delta/alpha ratio indicator following neurofeedback. CONCLUSIONS Preliminary findings suggest the efficacy of app-based remote neurofeedback in improving mental health, given the reduced symptom severity from pre- to postassessment for general psychological health, ADHD, anxiety, and depression, as well as adjusted resting EEG neural markers for individuals with symptoms of ADHD. Collectively, this supports the utility of the in-app assessment in monitoring behavioral and neural indices of mental health.
... Neurofeedback training (NFT) is considered a primary or supplementary treatment for a number of disorders, including attention-deficit/hyperactivity disorder (ADHD) [1][2][3][4][5], anxiety [6][7][8][9], and depression [7,8,10]. The American Academy of Pediatrics [11] provided a "level 1 best support" rating of NFT as a safe and effective evidence-based therapy for childhood ADHD. ...
... Neurofeedback training (NFT) is considered a primary or supplementary treatment for a number of disorders, including attention-deficit/hyperactivity disorder (ADHD) [1][2][3][4][5], anxiety [6][7][8][9], and depression [7,8,10]. The American Academy of Pediatrics [11] provided a "level 1 best support" rating of NFT as a safe and effective evidence-based therapy for childhood ADHD. ...
... Independent-samples t tests were conducted for each power ratio across groups (ie, healthy and abnormal values). Frequency bands were defined as follows: delta (1-4 Hz), theta (4-8 Hz), alpha (8)(9)(10)(11)(12)(13), and beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). These were averaged across frontal electrodes (ie, F3 and F4, based on the frontal nodes of the frontoparietal network [25,72] and the prevalence of a clean EEG signal) during the eyes-closed condition. ...
Article
Background Neurofeedback training (NFT) has been shown to be effective in treating several disorders (eg, attention-deficit/hyperactivity disorder [ADHD], anxiety, and depression); however, little is currently known regarding the effectiveness of remote NFT systems. Objective This retrospective study provides real-world data (N=593) to assess the efficacy of app-based remote NFT in improving brain health and cognitive performance. Methods Improvement was measured from pre- to postintervention of in-app assessments that included validated symptom questionnaires (the 12-item General Health Questionnaire, the ADHD Rating Scale IV, the Adult ADHD Self-Report Scale, the 7-item Generalized Anxiety Disorder scale, and the 9-item Patient Health Questionnaire), a cognitive test of attention and executive functioning (ie, continuous performance task), and resting electroencephalography (EEG) markers. Clinically significant improvement was evaluated using standard approaches. Results The greatest improvement was reported for the anxiety questionnaire, for which 69% (68/99) of participants moved from abnormal to healthy score ranges. Overall, adult and child participants who engaged in neurofeedback to improve attention and executive functions demonstrated improved ADHD scores and enhanced performance on a cognitive (ie, response inhibition) task. Adults with ADHD additionally demonstrated elevated delta/alpha and theta/alpha ratios at baseline and a reduction in the delta/alpha ratio indicator following neurofeedback. Conclusions Preliminary findings suggest the efficacy of app-based remote neurofeedback in improving mental health, given the reduced symptom severity from pre- to postassessment for general psychological health, ADHD, anxiety, and depression, as well as adjusted resting EEG neural markers for individuals with symptoms of ADHD. Collectively, this supports the utility of the in-app assessment in monitoring behavioral and neural indices of mental health.
... 21,22 Neurofeedback can be used in the treatment of depression, anxiety. [23][24][25] Mood disorders, 26,27 post-traumatic stress disorder, 28 treatment of offenders, 29 used obsessive-compulsive disorder treatment, 30 decreased pain perception 31 and increased intelligence and attention. 32 Narimani and Rajabi 33 investigated the effect of EEG biofeedback on reducing depression, anxiety, stress and tempting beliefs in people with substance abuse disorders. ...
... These results were consistent with previous findings. 16,23,24,25,26,27 Our findings show the effectiveness of neurofeedback therapy in reducing depression in women with chronic abdominal pain. Neurofeedback is effective in improving brain function and significantly improving the clinical symptoms of various disorders, including major depression. ...
Article
The aim of this study was to evaluate the effectiveness of neurofeedback therapy on depression, anxiety and stress in female patients with chronic clinical psychosomatic abdominal pain in Tabriz. This quasi-experimental study is a pre-test-post-test with a control group. The statistical population of this study was all women with chronic psychosomatic abdominal pain, from which a sample of 40 people was selected, from which the study was performed with 30 people (15 in the experimental group and 15 in the control group). These individuals were randomly assigned to two groups of 15 in the experimental group and the control group. In this intervention method, the experimental group underwent neurofeedback treatment for 10 weeks (three sessions of 40 minutes per week) and the control group did not receive any intervention and was placed on a waiting list. The experimental and control groups also completed the Depression, Anxiety and Stress Questionnaire in the pre-test and post-test. Analysis of MANCOVA was used to analyze the data. The results of analysis of MANCOVA showed that neurofeedback treatment was effective in reducing anxiety and depression (P <0.001). In other words, 53% of the changes in depression and 57% of the changes in anxiety were due to neurofeedback; but neurofeedback had no effect on stress. Neurofeedback was able to reduce depression and anxiety in women with abdominal pain but had no effect on their stress level. Keywords: Neurofeedback, depression, anxiety, stress, chronic psychosomatic abdominal pain.
... NF has now been implemented in a large number of studies assessing its effectiveness as an alternative or complementary treatment of a myriad of conditions including epilepsy (Sterman and Egner, 2006), attention-deficit hyperactivity disorder (ADHD; Gevensleben et al., 2009;Arns, Heinrich and Strehl, 2014), anxiety (Hammond, 2005), alcoholism (Saxby and Peniston, 1995), posttraumatic stress disorder (PTSD; Kluetsch et al., 2014;Kolk et al., 2016), mild head injuries (Byers, 1995), learning disabilities (Fernandez et al., 2003), stroke (Shindo et al., 2011), depression (Hammond, 2005), autistic spectrum disorder (Coben, Linden and Myers, 2009), tinnitus (i.e., chronic ear ringing that significantly interferes with daily tasks; Dohrmann et al., 2007), recurrent migraine headaches (Walker, 2011), etc. Furthermore, NF can present interesting applications for healthy populations as well, by enhancing well-being (Kluetsch et al., 2014), memory, attention, cognitive performance (Zoefel, Huster and Herrmann, 2011;Nan et al., 2012;Wang and Hsieh, 2013), or peak performance (Hammond, 2007). ...
... NF has now been implemented in a large number of studies assessing its effectiveness as an alternative or complementary treatment of a myriad of conditions including epilepsy (Sterman and Egner, 2006), attention-deficit hyperactivity disorder (ADHD; Gevensleben et al., 2009;Arns, Heinrich and Strehl, 2014), anxiety (Hammond, 2005), alcoholism (Saxby and Peniston, 1995), posttraumatic stress disorder (PTSD; Kluetsch et al., 2014;Kolk et al., 2016), mild head injuries (Byers, 1995), learning disabilities (Fernandez et al., 2003), stroke (Shindo et al., 2011), depression (Hammond, 2005), autistic spectrum disorder (Coben, Linden and Myers, 2009), tinnitus (i.e., chronic ear ringing that significantly interferes with daily tasks; Dohrmann et al., 2007), recurrent migraine headaches (Walker, 2011), etc. Furthermore, NF can present interesting applications for healthy populations as well, by enhancing well-being (Kluetsch et al., 2014), memory, attention, cognitive performance (Zoefel, Huster and Herrmann, 2011;Nan et al., 2012;Wang and Hsieh, 2013), or peak performance (Hammond, 2007). ...
Thesis
Full-text available
Over the last 30 years we have observed dramatic declines in mental health worldwide, with nearly 450 million people currently suffering from a mental or behavioral disorder. Globally, there is less than 1 mental health professional for every 10,000 people, with 76-85% of the population in low and middle-income countries without access to treatment. The overarching aim of this thesis is the identification of novel and cost-effective methods for measuring, detecting, and assessing well-being. In the first study of this research project, we validated the ability of a quick global scale to capture multidimensional well-being on 1,615 participants that participated in an online survey, identified some predictors of well-being, and observed improvements from online interventions. Mental health and individual well-being also influences the structure and function of our brains across the lifespan, which in turn, mediate well-being levels. While progress has been made regarding our understanding of the interacting relationships between well-being and brain function, much is still unknown. Recent technological advances have led to the development of affordable, light-weight, wearable, and wireless electroencephalography (EEG) technologies that offer fast preparation time, high mobility, and that facilitate the collection of EEG data over large and diversified populations by increasing access to populations that were previously difficult to study with conventional systems. The analysis of large datasets with robust statistical methods or advanced machine-learning algorithms can ease the identification of trends, the mediator role of covariables, and the classification of mental states. While low-cost, low-density EEG systems have presented significant challenges for conducting EEG research, here we validated a wearable system for recording spectral measures relevant to the study of well-being, by comparison with a state-of-the-art system (study 2). In study 3, we used the tools validated in studies 1 and 2 to examine the relation between EEG and multidimensional well-being in a large sample (N = 353). We found a potential EEG marker of well-being, consistent with some literature on anxiety and depression, with age as a mediator. We discuss interpretations and limitations related to the studies and the broader field, as well as future directions (e.g., real-world EEG monitoring, dyadic or multimodal applications, brain-computer interfaces, neurofeedback training) and ethical implications for the field. The broader applications of this line of research will hopefully help to reduce the prevalence of mental health disparities worldwide (e.g., chronic stress, anxiety disorder, depression, psychiatric conditions), and will also help to predict and prevent mental illness in the broader population.
... At present, the most studied of BCI in the field of education is the neural feedback training technology for improving concentration (Heinrich, Gevensleben, & Strehl, 2007;Hammond, 2005). Specifically, after quantifying the cognitive state of brain, it is transformed into the signals that can be perceived by the perception system through form conversion, such as sound, light, image, etc. Users adjust the intensity of the perceived signal by controlling the concentration state inside their brain, so as to improve the concentration of brain. ...
... It enables a person to alter their cortical electrical activity through real-time feedback. Alphatheta training has been effectively used to treat AD (Abdian et al., 2021;Hammond, 2005;Moore, 2000). EEG-NFT works on the electrophysiology of brain by synchronizing random electrical activity through training specific electrical waves repeatedly over a period of time. ...
... Utvrđeno je da je neurofeedback učinkovit u modificiranju moždanih funkcija i stvaranju značajnih poboljšanja u kliničkim simptomima kod djece, adolescenata i odraslih koji imaju razne poremećaje kao što su npr. epilepsija, ADHD, teškoće učenja (Hammond, 2005). Prva istraživanja primjene neurofeedback-a počela su se provoditi 1970-ih godina (Enriquez-Geppert, Smit, Garcia-Pimenta, Arns, 2019). ...
Conference Paper
Full-text available
The main objective of this paper was to define the differences in the effects of traditional strength bodyweight training matched load weight training with kettlebells. Forty young karate athletes aged 10 to 14 were divided in two experimental groups: standard experimental group 1 (EKS 1) – strength training with bodyweight (n=20), and experimental group 2 (EKS 2) (n=20)– strength kettlebell training. All respondents were subjected to anthropometric measurement and twelve motoric tests (coordination, three repetitive strength, and segmental movement speed tests, three each), to determine the difference of effects on motor abilities. Both groups had frequency of two training sessions a week during six weeks period. Groups were matched by training load parameters, with the weight added training being the only difference in EKS 2. The results measurement showed that the EKS 1 significantly progressed in four motoric tests: (1 test trivial effect, 2 tests small effect, 1 test moderateeffect). EKS 2 achieved significantlyhigher effects, with statistically significant progress in applied motoric tests (1 trivial effect, 7 tests small effects, and 4 tests moderate effects). The results of this research show progress inmotor abilities for both strength training groups, with more significant changes observed in the group with additional weight load, confirming the justifiability of the application of kettlebell as additional load in young karate athletes. Keywords: weight training, bodyweight training, kettlebell
... The focus was on beta-band power along the midline (cFz-cPz electrodes). Clinical research shows that an excess of such beta activity is associated with an increase in state anxiety [25]. Specifically, the aim of the study is to perform a comparison between two neurofeedback conditions (in a within-subject design): a) Cognitive Reappraisal (CR) task; b) Emotional Acceptance (EA) task. ...
... The above brief review of qEEG features and properties and their association with neuropsychopathology suggests the existence of circular causality, where, on the one hand, different pathological processes affect the qEEG pattern and, on the other hand, changes in the qEEG pattern affect pathological processes. This supposition is supported by converging empirical evidence: (a) central nervous system (CNS)-active drugs that affect known neuromediators change different features of the qEEG oscillatory pattern in a consistent and predictable manner, with a parallel reduction in symptoms [360][361][362][363]; (b) specific features of the qEEG oscillatory pattern have better predictive power for medication response compared to a syndrome-based diagnosis [364][365][366][367][368][369][370][371]; for example, the overall predictive accuracy in differentiating treatment responders from non-responders is 84%, with a sensitivity of 77% and a specificity of 92% [372]; (c) different features of the qEEG oscillatory pattern predict future (i) decline within the next 7 years in normal elderly people with subjective cognitive complains (no objective evidence of cognitive deficit) [259], (ii) clinical outcomes in patients in the vegetative state 6 years after brain injury [315,327], and (iii) developments of delinquent (antisocial) behavior [373]; (d) normalization of the distorted structure of the qEEG oscillatory pattern by an exogenous magnetic field stimulation changes the subjective experience of neuropsychopathology, accompanied by a clinical decrease (>50% reduction) of symptom severity [374] (see also [375,376]); (e) normalization of atypical qEEG oscillatory patterns through operant conditioning with neurofeedback results in symptom reduction in neuropsychopathologies such as epilepsy [377,378], depression and anxiety [379], schizophrenia [380], addiction [381], ADHD [382,383], sleep disorders [384], autism [385], chronic pain [386], learning difficulties [387], and dyslexia [388]; last but not least, (f) cognitive enhancement in the elderly by qEEG neurofeedback [389,390]. ...
Article
Full-text available
Many practicing clinicians are time-poor and are unaware of the accumulated neuroscience developments. Additionally, given the conservative nature of their field, key insights and findings trickle through into the mainstream clinical zeitgeist rather slowly. Over many decades, clinical, systemic, and cognitive neuroscience have produced a large and diverse body of evidence for the potential utility of brain activity (measured by electroencephalogram—EEG) for neurology and psychiatry. Unfortunately, these data are enormous and essential information often gets buried, leaving many researchers stuck with outdated paradigms. Additionally, the lack of a conceptual and unifying theoretical framework, which can bind diverse facts and relate them in a meaningful way, makes the whole situation even more complex. To contribute to the systematization of essential data (from the authors’ point of view), we present an overview of important findings in the fields of electrophysiology and clinical, systemic, and cognitive neuroscience and provide a general theoretical–conceptual framework that is important for any application of EEG signal analysis in neuropsychopathology. In this context, we intentionally omit detailed descriptions of EEG characteristics associated with neuropsychopathology as irrelevant to this theoretical–conceptual review.
Article
Conventional treatment for individuals with histories of sexual offending has typically involved the facilitation of cognitive-behavioral interventions. Recent research related to this form of intervention has raised concerns about its effectiveness. Neurofeedback has been found to be a beneficial form of treatment for a range of clinical presentations internationally. Despite this, its use in the UK has thus far been limited. Based on the theoretical literature related to sexual offending, as well as findings that Neurofeedback can be beneficial for people who experience problems resulting from trauma, emotional instability, harmful behaviors toward others, those with developmental disorders, and for those who have struggled to engage with and/or benefit from talking therapies. Neurofeedback was carried out with an individual in a UK-based secure mental health setting. This individual, referred to as John in the current study, presented to services with an Autism Spectrum Condition, mild Intellectual Disability and a diagnosis of pedophilia, as well as a history of sexual offending against children and vulnerable adults. John had engaged in many treatment programs over many years with little evidence of significant benefit. Psychometric measures as well as qualitative feedback was used to evaluate any change experienced by John following Neurofeedback and the use of the Reliable Change Index revealed significant improvements in relation to depression, anxiety, obsessive-compulsive type patterns of responding, child sexual arousal, sexual compulsivity, and sexual preoccupation. Whilst our findings are modest they do provide tentative support for the use of Neurofeedback for people with similar presenting difficulties to John and those in similar circumstances. Implications and recommendations are discussed.
Article
Full-text available
Biofeedback-assisted modulation of electrocortical activity has been established to have intrinsic clinical benefits and has been shown to improve cognitive performance in healthy humans. In order to further investigate the pedagogic relevance of electroencephalograph (EEG) biofeedback (neurofeedback) for enhancing normal function, a series of investigations assessed the training's impact on an ecologically valid real-life behavioural performance measure: music performance under stressful conditions in conservatoire students. In a pilot study, single-blind expert ratings documented improvements in musical performance in a student group that received training on attention and relaxation related neurofeedback protocols, and improvements were highly correlated with learning to progressively raise theta (5–8 Hz) over alpha (8–11 Hz) band amplitudes. These findings were replicated in a second experiment where an alpha/theta training group displayed significant performance enhancement not found with other neurofeedback training protocols or in alternative interventions, including the widely applied Alexander technique.
Chapter
The formal application of behavioral conditioning techniques for therapeutic purposes in epilepsy is of relatively recent origin. A comprehensive review of this area of investigation is currently being prepared for publication by Mostofsky and Balaschak at Boston University. One of the first definitive papers on this subject, however, appeared in the mid-50s when Efron reported the interruption and eventual elimination of generalized tonic-clonic seizures in one female patient with a 26-year history of the disorder. This patient experienced a well-developed aura which was inevitably followed by a grand mal seizure. When a specific sensory stimulus (strong, unpleasant odor) was applied early in the aura, Efron (1956) reported that further seizure development was consistently prevented. Application of the stimulus late in the aura resulted either in a partial seizure or a failure to abort. In further studies on this patient, Efron (1957) successfully paired the olfactory stimulus to a nonspecific visual stimulus consisting of a silver bracelet. Staring at this bracelet for several moments soon became effective in preventing seizure development, and eventually simply thinking about it was sufficient. This patient remained free of clinical seizures for 14 months. During the later months of this follow-up period the incidence of warning auras had sharply decreased, also, in spite of complete withdrawal of anticonvulsant medication.
Chapter
Obsessive compulsive disorder (OCD) has been the subject of a growing body of biologically oriented psychiatric research. There is mounting evidence for a neurobiological basis for OCD. Early studies of the conventional electroencephalogram (EEG) generally showed a higher prevalence of abnormal records in obsessional patients (Pacella et al. 1944; Rockwell 1847). Using quantitative EEG (QEEG) in obsessional patients, Flor-Henry et al. (1979) noted abnormalties in the left temporal region.